| Paper: | IMDSP-P7.12 | ||
| Session: | Indexing and Retrieval | ||
| Time: | Wednesday, May 19, 15:30 - 17:30 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Image and Video Indexing and Retrieval | ||
| Title: | INTERACTIVE IMAGE RETRIEVAL BY QUERY FUSION | ||
| Authors: | Azadeh Kushki; University of Toronto | ||
| Panagiotis Androutsos; University of Toronto | |||
| Anastasios Venetsanopoulos; University of Toronto | |||
| Abstract: | The use of low-level visual features such as colour and shape incontent-based image retrieval system leads to several ambiguities.Specifically, due to the many-to-many mapping between thelow-level feature space and high-level user concepts, a conceptualuser query may not be modelled as a single point in the featurespace. Furthermore, conceptually similar images may not be fallclose to each other in the low-level feature space. This workaddresses these issues by proposing an interactive technique,Query Feedback. This method employs user input to represent ahigh-level conceptual query as various points in the low-levelspace. Thus, similarity to a given conceptual query is obtained asthe fusion of several low-level representations in the featurespace. | ||
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